In this page, we showed:

• The relationship between the Marijuana use and marijuana lyric trends

• Mean prevalence rates (%) of Marijuana/other than Marijuana/binge drinking use by age group

• Risk perception on smoking marijuana once a month

• Annual incidence of first use of marijuana

---
title: "drug dashboard"
output: 
  flexdashboard::flex_dashboard:
    orientation: columns
    vertical_layout: scroll
    source_code: embed
---
In this page, we showed:

- The relationship between the Marijuana use and marijuana lyric trends

- Mean prevalence rates (%) of Marijuana/other than Marijuana/binge drinking use by age group 

- Risk perception on smoking marijuana once a month

- Annual incidence of first use of marijuana


```{r setup, include=FALSE}
library(flexdashboard)
library(plotly)
library(tidyverse)
```

```{r}
songs_abuse=read_csv("./data/songs_abuse.csv")
```

Column {.tabset data-width=600}
-----------------------------------------------------------------------

### Marijuana use Vs % of marijuana lyric national level

```{r}
songs_abuse_plot=
  songs_abuse%>%
  filter(stname=="National", outcome=="Marijuana use in the past month")%>%
  group_by(year)%>%
  ggplot(aes(x = p_lyrics, y = bsae, color = agegrp)) +
    geom_point() +
    geom_smooth(aes(group = agegrp), se = F) +
   labs(title = "Marijuana use Vs % of marijuana lyric national level",
         y = "Marijuana use in the past(%)",
         color = "agegroup")

ggplotly(songs_abuse_plot)
```

Column {.tabset data-width=400}
-----------------------------------------------------------------------

### Mean prevalence rates (%) of Marijuana use by age group 

```{r}
marijuana_plot=
songs_abuse%>%
  filter(outcome=="Marijuana use in the past month",area==0)%>%
  group_by(year,agegrp)%>%
  summarize(
  mean_bsae = mean(bsae)
)%>%
  ggplot(aes(x = year, y = mean_bsae)) +
  geom_smooth(aes(color = agegrp), alpha = .5)+
    labs(title = "Mean prevalence rates (%) of Marijuana use by age group",
         y = "Mean prevalence rates of Marijuana use (%) ",
         color = "agegroup")

ggplotly(marijuana_plot)
```

### Mean prevalence rates (%) of illicit drug other than marijuana by age group

```{r}
otherthan_marijuana_plot=
  songs_abuse%>%
  filter(outcome=="Illicit drugs other than marijuana use in the last month",area==0)%>%
  group_by(year,agegrp)%>%
  summarize(
  mean_bsae = mean(bsae)
)%>%
  ggplot(aes(x = year, y = mean_bsae)) +
  geom_smooth(aes(color = agegrp), alpha = .5)+
  labs(title = "Mean prevalence rates (%) of illicit durg other than marijuana by age group",
         y = "Mean prevalence rates (%) of illicit durg other than marijuana",
         color = "agegroup")

ggplotly(otherthan_marijuana_plot)
```

### Mean prevalence rates (%) of binge drinking by age group
```{r}
bingedrink_plot=
songs_abuse%>%
  filter(outcome=="Binge drinking in the last month",area==0)%>%
  group_by(year,agegrp)%>%
  summarize(
  mean_bsae = mean(bsae)
)%>%
  ggplot(aes(x = year, y = mean_bsae)) +
  geom_smooth(aes(color = agegrp), alpha = .5)+
  labs(title = "Mean prevalence rates (%) of binge drinking in the past by age group",
         y = "Mean binge drinking (%) in the past",
         color = "agegroup")

ggplotly(bingedrink_plot)
```


### Risk perception on smoking marijuana once a month
```{r}
risk_plot=
songs_abuse%>%
  filter(outcome=="Risk perception on smoking marijuana once a month",area==0)%>%
  group_by(year,agegrp)%>%
  summarize(
  mean_bsae = mean(bsae)
)%>%
  ggplot(aes(x = year, y = mean_bsae)) +
  geom_smooth(aes(color = agegrp), alpha = .5)+
  labs(title = "Risk perception on smoking marijuana by age group",
         y = "Risk perception on smoking marijuana(%) ",
         color = "agegroup")

ggplotly(risk_plot)
```

### Annual incidence of first use of marijuana
```{r}
incidence_plot=
songs_abuse%>%
  filter(outcome=="Annual incidence of first use of marijuana",area==0)%>%
  group_by(year,agegrp)%>%
  summarize(
  mean_bsae = mean(bsae)
)%>%
  ggplot(aes(x = year, y = mean_bsae)) +
  geom_smooth(aes(color = agegrp), alpha = .5)+
  labs(title = "Annual incidence of first use of marijuana by age group",
         y = "Annual incidence of first use of marijuana (%) ",
         color = "agegroup")
ggplotly(incidence_plot)
```